Automotive predictive failure system
First Claim
1. A method of determining a predictive failure for vehicular component comprises the steps of:
- (A) providing a vehicle with a plurality of part sensors and an on-board computing (OBC) device, wherein each part sensor is communicably coupled with the OBC device;
(B) providing at least one remote server, wherein the remote server is communicably coupled with the OBC device;
(C) providing a primary dataset and a secondary dataset for each part sensor, wherein the primary dataset is associated with an active performance-defined range, and wherein the secondary dataset is associated with an updatable total time duration;
(D) timestamping and uploading a performance time-dependent data (PTDD) point from each part sensor to the remote server;
(E) sorting the PTDD point into the secondary dataset with the remote server, if the PTDD point is outside the active performance-defined range, and if the primary dataset is empty;
(F) sorting the PTDD point into the primary dataset with the remote server, if the PTDD point is within the active performance-defined range, or if the primary dataset is not empty;
(G) repeating steps (C) through (F) throughout each after-initial trip completed by the vehicle in order to populate the primary dataset and the secondary dataset for each part sensor with a plurality of PTDD points;
storing each of the plurality of PTDD points for each part sensor on the OBC device at a recording time interval during step (G), timestamping each of the plurality of PTDD points with a logging time during step (G), and discretely and sequentially sending the plurality of PTDD points from the OBC device to the remote server at an uploading time interval, wherein the uploading time interval is greater than or equal the recording time interval; and
(H) identifying a potential vehicular problem during an arbitrary trip with the remote server, if an actual total time period for the secondary dataset is not equal to the updatable total time duration during the arbitrary trip, or if an arbitrary PTDD point within the primary dataset is outside of the active performance-defined range during the arbitrary trip, wherein the arbitrary trip is any one of the plurality of after-initial trips.
0 Assignments
0 Petitions
Accused Products
Abstract
A method of predicting failure for vehicular components is implemented within a vehicle through a plurality of part sensors and an on-board computing (OBC) device as the part sensors are communicably coupled with a remote server through the OBC device. The OBC device continuously timestamps and uploads a plurality of performance time-dependent data (PTDD) points to the remote server throughout a current vehicular trip. The remote server then analyzes the uploaded PTDD points with an updatable total time duration and an active performance-define range that are calculated from prior vehicular trips. The remote server is then able to identify a potential vehicular problem during the current trip, based upon the uploaded PTDD points. When a potential vehicular problem is detected within the current trip, an annotating assessment is generated and wirelessly sent to a personal computing device of the owner/operator of the vehicle.
-
Citations
32 Claims
-
1. A method of determining a predictive failure for vehicular component comprises the steps of:
-
(A) providing a vehicle with a plurality of part sensors and an on-board computing (OBC) device, wherein each part sensor is communicably coupled with the OBC device; (B) providing at least one remote server, wherein the remote server is communicably coupled with the OBC device; (C) providing a primary dataset and a secondary dataset for each part sensor, wherein the primary dataset is associated with an active performance-defined range, and wherein the secondary dataset is associated with an updatable total time duration; (D) timestamping and uploading a performance time-dependent data (PTDD) point from each part sensor to the remote server; (E) sorting the PTDD point into the secondary dataset with the remote server, if the PTDD point is outside the active performance-defined range, and if the primary dataset is empty; (F) sorting the PTDD point into the primary dataset with the remote server, if the PTDD point is within the active performance-defined range, or if the primary dataset is not empty; (G) repeating steps (C) through (F) throughout each after-initial trip completed by the vehicle in order to populate the primary dataset and the secondary dataset for each part sensor with a plurality of PTDD points; storing each of the plurality of PTDD points for each part sensor on the OBC device at a recording time interval during step (G), timestamping each of the plurality of PTDD points with a logging time during step (G), and discretely and sequentially sending the plurality of PTDD points from the OBC device to the remote server at an uploading time interval, wherein the uploading time interval is greater than or equal the recording time interval; and (H) identifying a potential vehicular problem during an arbitrary trip with the remote server, if an actual total time period for the secondary dataset is not equal to the updatable total time duration during the arbitrary trip, or if an arbitrary PTDD point within the primary dataset is outside of the active performance-defined range during the arbitrary trip, wherein the arbitrary trip is any one of the plurality of after-initial trips. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
-
Specification